Computation of realistic virtual phantom images for an objective lesion detectability assessment in digital mammography

Image quality assessment is required for an optimal use of mammographic units. On the one hand, there are objective image quality assessment methods based on the measurement of technical parameters such as modulation transfer function (MTF), noise power spectrum (NPS) or detection quantum efficiency (DQE) describing performances of digital detectors. These parameters are, however, without direct relationship with lesion detectability in clinical practice. On the other hand, there are image quality assessment methods involving time consuming procedures, but presenting a direct relationship with lesion detectability. This contribution describes an X-ray source/digital detector model leading to the simulation of virtual contrast-detail phantom (CDMAM) images. The virtual image computation method requires the acquisition of only few real images and allows for an objective image quality assessment presenting a direct relationship with lesion detectability. The transfer function of the proposed model takes as input physical parameters (MTF* and noise) measured under clinical conditions on mammographic units. As presented in this contribution, MTF* is a modified MTF taking into account the effects due to X-ray scatter in the breast and magnification. Results obtained with the structural similarity index prove that the simulated images are quite realistic in terms of contrast and noise. Tests using contrast detail curves highlight the fact that the simulated and real images lead to very similar data quality in terms of lesion detectability. Finally, various statistical tests show that quality factors computed for both the simulated images and the real images are very close for the two data sets.     

Quantification of Al-equivalent thickness of just visible microcalcifications in full field digital mammograms

Characterization of digital mammography systems is often performed by means of contrast-detail curves using a homogeneous phantom with inserts of different sizes and thicknesses. In this article, a more direct measure of the threshold contrast-detail characteristics of microcalcifications in clinical mammograms is proposed, which also takes into account routine processing and display. The proposed method scores the detectability of simulated microcalcifications with known size and aluminum-equivalent thickness. Thickness estimates, based on x-ray transmission coefficients, were first validated for Al particles. The same approach was then applied to associate Al-equivalent thickness with simulated microcalcifications. Thirty-five mammograms of patients were acquired using a full field digital mammography (FFDM) system operating under standard exposure conditions. Different microcalcifications were simulated using templates of real microcalcifications as described in Med. Phys. 30, 2234-2240 (2003). These templates were first modified such that they simulated a template of the same microcalcification for an ideally sharp detector. They were then adjusted for the imaging characteristics of the FFDM, beam quality, and breast thickness. Microcalcification sizes in the image plane ranged from 200 to 800 microm. Their peak Al-equivalent thickness varied between 70 and 1000 microm. Software phantoms were created. They consisted of 0-10 simulated microcalcifications randomly distributed in 2 cm by 2 cm frames embedded within digital mammograms. Routine processing and printing followed. Three experienced radiologists recorded the locations of the microcalcifications, and confidence ratings were given. Free response receiver operating characteristics (FROC) analysis was performed. Using a binary score, the fractions of detected microcalcifications were plotted as a function of equivalent diameter for the different Al-equivalent thicknesses. Pair-wise agreement of the detected microcalcifications was calculated for the different Al-equivalent thickness groups. The FROC curves of each radiologist indicated similar true positive fractions for a given number of false positives per image. One radiologist applied a more conservative scoring. Detected fractions for the different sizes of the microcalcifications showed the same trend for all observers. In addition, the observer with the least FP also detected less microcalcifications. The pair-wise agreement of the detected microcalcifications was good. The average detected fractions were >0.5 for microcalcifications with equivalent diameter >400 microm and Al-equivalent thickness >400 microm. An average detected fraction >0.5 was also seen for microcalcifications with equivalent diameter <400 microm and equivalent thickness >800 microm. The detected fractions of smaller microcalcifications were <0.5. The results obtained with this method indicate that it may be possible to quantify the performance of a digital mammography detector including processing and viewing for the detection of microcalcifications. We hypothesize that the FROC curves and detected fractions of simulated microcalcifications of different sizes reflect the clinical reality.     

An improved method for simulating microcalcifications in digital mammograms

The assessment of the performance of a digital mammography system requires an observer study with a relatively large number of cases with known truth which is often difficult to assemble. Several investigators have developed methods for generating hybrid abnormal images containing simulated microcalcifications. This article addresses some of the limitations of earlier methods. The new method is based on digital images of needle biopsy specimens. Since the specimens are imaged separately from the breast, the microcalcification attenuation profile scan is deduced without the effects of over and underlying tissues. The resulting templates are normalized for image acquisition specific parameters and reprocessed to simulate microcalcifications appropriate to other imaging systems, with different x-ray, detector and image processing parameters than the original acquisition system. This capability is not shared by previous simulation methods that have relied on extracting microcalcifications from breast images. The method was validated by five experienced mammographers who compared 59 pairs of simulated and real microcalcifications in a two-alternative forced choice task designed to test if they could distinguish the real from the simulated lesions. They also classified the shapes of the microcalcifications according to a standardized clinical lexicon. The observed probability of correct choice was 0.415, 95% confidence interval (0.284, 0.546), showing that the radiologists were unable to distinguish the lesions. The shape classification revealed substantial agreement with the truth (mean kappa = 0.70), showing that we were able to accurately simulate the lesion morphology. While currently limited to single microcalcifications, the method is extensible to more complex clusters of microcalcifications and to three-dimensional images. It can be used to objectively assess an imaging technology, especially with respect to its ability to adequately visualize the morphology of the lesions, which is a critical factor in the benign versus malignant classification of a lesion detected in screening mammography.     

Contrast-detail assessment of computed tomography scanners

The design and construction of contrast-detail detectability phantoms for the assessment of the imaging performance of CT scanners are described. These phantoms have been employed to undertake a series of measurements on a number of different machines. The results are expressed in terms of object contrast which is consistent with the conventional definition of radiological contrast. For one particular scanner, the imaging performance of a number of image reconstruction and post-processing filters has been investigated. The results indicate that there was no observed energy dependence of contrast-detail detectability once differences in technique factors and attenuation were taken into account. A similar conclusion was drawn from the results of a set of measurements made to examine the effect on detectability of additional filtration.     

Image quality assessment in digital mammography: part II. NPWE as a validated alternative for contrast detail analysis

Assessment of image quality for digital x-ray mammography systems used in European screening programs relies mainly on contrast-detail CDMAM phantom scoring and requires the acquisition and analysis of many images in order to reduce variability in threshold detectability. Part II of this study proposes an alternative method based on the detectability index (d') calculated for a non-prewhitened model observer with an eye filter (NPWE). The detectability index was calculated from the normalized noise power spectrum and image contrast, both measured from an image of a 5 cm poly(methyl methacrylate) phantom containing a 0.2 mm thick aluminium square, and the pre-sampling modulation transfer function. This was performed as a function of air kerma at the detector for 11 different digital mammography systems. These calculated d' values were compared against threshold gold thickness (T) results measured with the CDMAM test object and against derived theoretical relationships. A simple relationship was found between T and d', as a function of detector air kerma; a linear relationship was found between d' and contrast-to-noise ratio. The values of threshold thickness used to specify acceptable performance in the European Guidelines for 0.10 and 0.25 mm diameter discs were equivalent to threshold calculated detectability indices of 1.05 and 6.30, respectively. The NPWE method is a validated alternative to CDMAM scoring for use in the image quality specification, quality control and optimization of digital x-ray systems for screening mammography.     

A Technique for Simulating the Effect of Dose Reduction on Image Quality in Digital Chest Radiography

Purpose: The purpose of this study is to provide a pragmatic tool for studying the relationship between dose and image quality in clinical chest images. To achieve this, we developed a technique for simulating the effect of dose reduction on image quality of digital chest images. Materials and Methods: The technique was developed for a digital charge-coupled-device (CCD) chest unit with slot-scan acquisition. Raw pixel values were scaled to a lower dose level, and a random number representing noise to each specific pixel value was added. After adding noise, raw images were post processed in the standard way. Validation was performed by comparing pixel standard deviation, as a measure of noise, in simulated images with images acquired at actual lower doses. To achieve this, a uniform test object and an anthropomorphic phantom were used. Additionally, noise power spectra of simulated and actual images were compared. Also, detectability of simulated lesions was investigated using a model observer. Results: The mean difference in noise values between simulated and real lower-dose phantom images was smaller than 5% for relevant clinical settings. Noise power spectra appeared to be comparable on average but simulated images showed slightly higher noise levels for higher spatial frequencies and slightly lower noise levels for lower spatial frequencies. Comparable detection performance was shown in simulated and actual images with slightly worse detectability for simulated lower dose images. Conclusion: We have developed and validated a method for simulating dose reduction. Our method seems an acceptable pragmatic tool for studying the relationship between dose and image quality.     

Amorphous selenium flat panel detectors for digital mammography: validation of a NPWE model observer with CDMAM observer performance experiments

Model observers have been developed which incorporate a specific imaging task, system performance, and human observer characteristics and can potentially overcome some of the limitations in using detective quantum efficiency for optimization and comparison of detectors. In this paper, a modified nonprewhitening matched filter (NPWE) model observer was developed and validated to predict object detectability for an amorphous selenium (a-Se) direct flat-panel imager (FPI) where aliasing is severe. A preclinical a-Se digital mammography FPI with 85 microm pixel size was used in this investigation. Its physical imaging properties including modulation transfer function (MTF), noise power spectrum, and DQE were fully characterized. An observer performance study was conducted by imaging the CDMAM 3.4 contrast-detail phantom designed specifically for digital mammography and presenting these images to a panel of seven observers. X-ray attenuation and scatter due to the phantom were determined experimentally for use in development of the model observer. The observer study results were analyzed via threshold averaging and signal detection theory (SDT) based techniques to produce contrast-detail curves where threshold contrast is plotted as a function of disk diameter. Validity of the model was established using SDT analysis of the experimental data. The effect of aliasing on the detectability of small diameter disks was determined using the NPWE model observer. The signal spectrum was calculated using the presampling MTF of the detector with and without including the aliased terms. Our results indicate that the NPWE model based on Fourier domain parameters provides reasonable prediction of object detectability for the signal-known-exactly task in uniform image noise for a-Se direct FPI.     

Microcalcification detection using cone-beam CT mammography with a flat-panel imager

The purpose of this study was to investigate microcalcification detectability using CT mammography with a flat-panel imager. To achieve this, a computer simulation was developed to model an amorphous-silicon, CsI based flat-panel imager system using a linear cascaded model. The breast was modelled as a hemi-ellipsoid shape with composition of 50% adipose and 50% glandular tissue. Microcalcifications were modelled as small spheres having a composition of calcium carbonate. The results show that with a mean glandular dose equivalent to that typically used in two-view screening mammography, CT mammography with a flat-panel detector is capable of providing images where most microcalcifications are detectable. A receiver operating characteristic (ROC) study was conducted by five physicist observers viewing simulated CT mammography reconstructions. The results suggest that the microcalcification with its diameter equal to or greater than 0.175 mm can be detected with an average area under the ROC curve (AUC) greater than 0.95 using 0.1 or 0.2 mm pixelized detectors. The results also indicate that the optimal pixel size of the detector is around 0.2 mm for microcalcification detection, based on the trade-off between detectability of microcalcifications and the time required for data acquisition and reconstruction.     

Progression in diagnostic pathology; development of virtual microscopy and its applications

Many systems have already been designed and successfully used for clinical laboratory and pathological examination. The evolution of image analysis was enabled when analog images of the original glass slides could be transferred to digital images with the rapid development of virtual microscopy and virtual slides depended upon computer technologies. Today, whole slide can be acquired by virtual microscopes. The applications of virtual microscopy and virtual slides for teaching, diagnosis, telepathology, and research are more widely used than those of real microscope and real glass slides. In traditional cancer diagnosis, pathologists examine biopsies to make diagnostic assessments largely based on two-dimensional cell morphology and tissue distribution. These assessments are subjective and often show considerable variability. However, automated cancer diagnostic system based on three-dimensional image analysis based on nuclear bulging sign enables objective judgments using quantitative measurements. We expect that the shortage of pathologists will be improved when an automated cancer diagnosis system is developed.     

Analyser-based mammography using single-image reconstruction

We implement an algorithm that is able to decode a single analyser-based x-ray phase-contrast image of a sample, converting it into an equivalent conventional absorption-contrast radiograph. The algorithm assumes the projection approximation for x-ray propagation in a single-material object embedded in a substrate of approximately uniform thickness. Unlike the phase-contrast images, which have both directional bias and a bias towards edges present in the sample, the reconstructed images are directly interpretable in terms of the projected absorption coefficient of the sample. The technique was applied to a Leeds TOR[MAM] phantom, which is designed to test mammogram quality by the inclusion of simulated microcalcifications, filaments and circular discs. This phantom was imaged at varying doses using three modalities: analyser-based synchrotron phase-contrast images converted to equivalent absorption radiographs using our algorithm, slot-scanned synchrotron imaging and imaging using a conventional mammography unit. Features in the resulting images were then assigned a quality score by volunteers. The single-image reconstruction method achieved higher scores at equivalent and lower doses than the conventional mammography images, but no improvement of visualization of the simulated microcalcifications, and some degradation in image quality at reduced doses for filament features.     

Multisphere phantom and analysis algorithm for PET image quality assessment

PET image quality measurements of lesion detectability frequently use a small, radioactive sphere in a larger phantom. The typical analysis of a small single sphere in background has several shortcomings as a measure for detectability and quantitation: the measurement has low statistical power; the region of interest (ROI) is susceptible to large pixel-to-pixel fluctuations; only a single point in the axial and transaxial field of view is analyzed; background noise measurements in regions away from the signal sphere may bias the detectability measurement and user-placed ROIs can cause inconsistent measurements. For a more robust measurement and repeatable analysis of small lesion detectability in PET images, a multisphere phantom and analysis algorithm were developed. The multisphere phantom consists of a collection of 50 1.0-cm spheres, mounting rods and a gridded plate. A PET/CT study is presented where 29 spheres with a 4:1 sphere-to-background radioactivity ratio were acquired for multiple frame durations and reconstructed. An analysis algorithm was implemented and applied to the acquired PET/CT that detects the contrast-enhanced spheres in a CT, places ROIs on the spheres and their respective proximal background, applies the ROIs to the PET and performs quantitation. Results are presented that show the impact of increasing number of signal spheres and of different background ROI placement methods on the image quality measurement. Increasing the number of spheres reduced the variability in the image quality measurements, but only up to a point, beyond which increasing the number of spheres did not considerably reduce the variability. A phantom with numerous spherical inserts increases several measurement aspects: the flexibility of sphere placement during setup, the number of radioactivity concentrations that can be used during a single study and the statistical power of measurements. Additionally, an automated algorithm that localizes spheres, places ROIs and performs quantitation will increase reliability and reproducibility of image quality assessment, in addition to simplifying the analysis.     

Automated assessment of low contrast sensitivity for CT systems using a model observer

Purpose: Low contrast sensitivity of CT scanners is regularly assessed by subjective scoring of low contrast detectability within phantom CT images. Since in these phantoms low contrast objects are arranged in known fixed patterns, subjective rating of low contrast visibility might be biased. The purpose of this study was to develop and validate a software for automated objective low contrast detectability based on a model observer.Methods: Images of the low contrast module of the Catphan 600 phantom were used for the evaluation of the software. This module contains two subregions: the supraslice region with three groups of low contrast objects (each consisting of nine circular objects with diameter 2-15 mm and contrast 0.3, 0.5, and 1.0%, respectively) and the subslice region with three groups of four circular objects each (diameter 3-9 mm; contrast 1.0%). The software method offered automated determination of low contrast detectability using a NPWE (nonprewhitening matched filter with an eye filter) model observer for the supraslice region. The model observer correlated templates of the low contrast objects with the acquired images of the Catphan phantom and a discrimination index d' was calculated. This index was transformed into a proportion correct (PC) value. In the two-alternative forced choice (2-AFC) experiments used in this study, a PC ≥ 75% was proposed as a threshold to decide whether objects were visible. As a proof of concept, influence of kVp (between 80 and 135 kV), mAs (25-200 mAs range) and reconstruction filter (four filters, two soft and two sharp) on low contrast detectability was investigated. To validate the outcome of the software in a qualitative way, a human observer study was performed.Results: The expected influence of kV, mAs and reconstruction filter on image quality are consistent with the results of the proposed automated model. Higher values for d' (or PC) are found with increasing mAs or kV values and for the soft reconstruction filters. For the highest contrast group (1%), PC values were fairly above 75% for all object diameters >2 mm, for all conditions. For the 0.5% contrast group, the same behavior was observed for object diameters >3 mm for all conditions. For the 0.3% contrast group, PC values were higher than 75% for object diameters >6 mm except for the series acquired at the lowest dose (25 mAs), which gave lower PC values. In the human observer study similar trends were found.Conclusions: We have developed an automated method to objectively investigate image quality using the NPWE model in combination with images of the Catphan phantom low contrast module. As a first step, low contrast detectability as a function of both acquisition and reconstruction parameter settings was successfully investigated with the software. In future work, this method could play a role in image reconstruction algorithms evaluation, dose reduction strategies or novel CT technologies, and other model observers may be implemented as well.     

Assessment of the effects of pixel loss on image quality in direct digital radiography

Modern digital radiographic 'flat panel' detectors can exhibit a progressive form of image degradation arising from non-functioning pixels. The effect of these 'dead pixels' on the quantitive image quality measures of modulation transfer function (MTF), noise power spectrum (NPS) and detective quantum efficiency (DQE) is investigated by a simulated degradation of images obtained from an Hologic EPEX system. The effects on the semi-quantitive measures obtained from contrast threshold test objects and resolution gratings are also investigated. Results suggest that the contrast-detail tests often employed in quality assurance measures are not sufficient to reveal the presence of dead pixels until well beyond the recommended replacement point for the flat panel detector. However, measurements of spatial resolution using a line pairs phantom were found to be more sensitive to pixel loss. Measurement of the MTF, NPS and DQE can reveal small changes in image quality with increasing pixel loss, with a distinctive pattern in the trend of the NPS.     

Evaluation of edge effect due to phase contrast imaging for mammography

It is well-known that the edge effect produced by phase contrast imaging results in the edge enhancement of x-ray images and thereby sharpens those images. It has recently been reported that phase contrast imaging using practical x-ray tubes with small focal spots has improved image sharpness as observed in the phase contrast imaging with x-ray from synchrotron radiation or micro-focus x-ray tubes. In this study, we conducted the phase contrast imaging of a plastic fiber and plant seeds using a customized mammography equipment with a 0.1 mm focal spot, and the improvement of image sharpness was evaluated in terms of spatial frequency response of the images. We observed that the image contrast of the plastic fiber was increased by edge enhancement, and, as predicted elsewhere, spectral analysis revealed that as the spatial frequencies of the x-ray images increased, so did the sharpness gained through phase contrast imaging. Thus, phase contrast imaging using a practical molybdenum anode tube with a 0.1 mm-focal spot would benefit mammography, in which the morphological detectability of small species such as microcalcifications is of great concern. And detectability of tumor-surrounded glandular tissues in dense breast would be also improved by the phase contrast imaging.     

Virtual electron microscopy: a simple implementation creating a new paradigm in ultrastructural examination

Ultrastructural examination is a time-consuming and tiring process, requiring search for diagnostic features on a low-contrast screen in a dim environment. This article describes a method to circumvent these problems through the creation of a virtual ultrathin slide. This can be achieved by automated capturing of hundreds of images at high magnification and stitching them together into a digital image with a resolution of 4 nm/pixel. The pathologist can then navigate the virtual slide at his/her workstation computer. The image shows good contrast and resolution for diagnostic purposes, and most important, the pathologist can precisely note where the specific ultrastructural features are located. The setup required to implement virtual electron microscopy includes a transmission electron microscope equipped with motorized stage and automated digital image capture function, 2 free software components, self-developed software, and a desktop-grade computer. Besides use in daily diagnosis, virtual electron microscopy can open up many new applications such as undergraduate teaching, pathology resident training, external quality assurance program, and expert consultation.     

Factors to keep in mind when introducing virtual microscopy

Digitization of glass slides and delivery of so-called virtual slides (VS) emulating a real microscope over the Internet have become reality due to recent improvements in technology. We have implemented a virtual microscope for instruction of medical students and for continuing medical education. Up to 30,000 images per slide are captured using a microscope with an automated stage. The images are post-processed and then served by a plain hypertext transfer protocol (http)-server. A virtual slide client (vMic) based on Macromedia's Flash MX, a highly accepted technology available on every modern Web browser, has been developed. All necessary virtual slide parameters are stored in an XML file together with the image. Evaluation of the courses by questionnaire indicated that most students and many but not all pathologists regard virtual slides as an adequate replacement for traditional slides. All our virtual slides are publicly accessible over the World Wide Web (WWW) at . Recently, several commercially available virtual slide acquisition systems (VSAS) have been developed that use various technologies to acquire and distribute virtual slides. These systems differ in speed, image quality, compatibility, viewer functionalities and price. This paper gives an overview of the factors to keep in mind when introducing virtual microscopy.Universal resource locators (URLs) visited at the time of writing (June 2005) may change or vanish with lapse of time. Therefore and because of usability, we have created a web page with all URLs that will be updated on a regular basis: .     

The use of multivariate regression analysis in contrast-detail studies of CT scanners

Previous studies of the imaging performance of computed tomography (CT) scanners, and other imaging modalities, have failed to apply appropriate statistical methods to data analysis, thus impairing the accuracy and significance of results. Given that imaging performance involves a number of interrelated variables and an element of randomness, its empirical assessment requires multivariate regression analysis. This method is used here to analyze anew a set of contrast-detail data from a previous study on CT scanners. The main issues considered are the specification of the proper functional form linking perceptibility, dose and contrast, the estimation of the contrast and dose coefficients, and of scanner-specific constants to be used in computing indices of imaging quality. One of the main empirical findings is that the dose coefficient of the CT scanners studied is significantly less than that predicted by the theoretical model: 1/5 instead of 1/3. This result suggests that actual dose used in routine clinical studies could be reduced substantially without impairing much the quality of the images. On the other hand, the coefficient of contrast does correspond to its predicted value, i.e., 2/3. The methodology used here is not limited to the contrast-detail framework, but is applicable to, and indeed essential in, empirical studies of the performance of any imaging modality.     

Dose efficiency and low-contrast detectability of an amorphous silicon x-ray detector for digital radiography

The effect of dose reduction on low-contrast detectability is investigated theoretically and experimentally for a production grade amorphous silicon (a-Si) x-ray detector and compared with a standard thoracic screen-film combination. A non-prewhitening matched filter observer model modified to include a spatial response function and internal noise for the human visual system (HVS) is used to calculate a signal-to-noise ratio (SNR) related to object detectability. Other inputs to the SNR calculation are the detective quantum efficiency (DQE) and the modulation transfer function (MTF) of the imaging system. Besides threshold detectability, the model predicts the equivalent perception dose ratio (EPDR), which is the fraction of the screen film exposure for which the digital detector provides equal detectability. Images of a contrast-detail phantom are obtained with the digital detector at dose levels corresponding to 27%, 41%, 63% and 100% of the dose used for screen-film. The images are used in a four-alternative forced choice (4-AFC) observer perception study in order to measure threshold detectability. A statistically significant improvement in contrast detectability is measured with the digital detector at 100% and 63% of the screen-film dose. There is no statistical difference between screen-film and digital at 41% of the dose. On average, the experimental EPDR is 44%, which agrees well with the model prediction of 40%.     

Impact of resolution and noise characteristics of digital radiographic detectors on the detectability of lung nodules

One of the unanswered questions in digital radiography is the connection between physical image quality metrics and clinical detection performance. In this paper, we examine the impact of two physical metrics, resolution and noise, on the detectability of nodules in a pulmonary background for specific digital radiographic detectors. A detection experiment was performed on a simulated image set using anatomical backgrounds from a high-quality lung radiograph and three different simulated nodule sizes (2-3.5 mm). The resolution and noise of the resulting images were modified using existing routines to simulate a selenium-based and a cesium iodide-based flat-panel detector at comparable exposures. A location-known-exactly (LKE) observer performance experiment was performed in which four experienced chest radiologists and three physicists specializing in chest radiology scored the images. The data from the observer experiment were analyzed by receiver operating characteristic (ROC) methodology. The detectability, as measured by the parameter Az, was higher for the selenium detector than the cesium iodide detector for all nodule sizes by an average of 8.5%. For one nodule size (2.75 mm), the difference between detectors was statistically significant (p < 0.01). The findings indicate that for the particular task studied, the superior resolution performance of the selenium-based detector provided better detectability of subtle lung nodules even though the images had greater noise than images obtained with the cesium iodide detector.     

A controlled phantom study of a noise equalization algorithm for detecting microcalcifications in digital mammograms

We report on some extensions and further developments of a well-known microcalcification detection algorithm based on adaptive noise equalization. Tissue equivalent phantom images with and without labeled microcalcifications were subjected to this algorithm, and analyses of results revealed some shortcomings in the approach. Particularly, it was observed that the method of estimating the width of distributions in the feature space was based on assumptions which resulted in the loss of similarity preservation characteristics. A modification involving a change of estimator statistic was made, and the modified approach was tested on the same phantom images. Other modifications for improving detectability such as downsampling and use of alternate local contrast filters were also tested. The results indicate that these modifications yield improvements in detectability, while extending the generality of the approach. Extensions to real mammograms and further directions of research are discussed.